Social Network Analysis Applied to Team Sports Analysis [recurso electrónico] / by Filipe Manuel Clemente, Fernando Manuel Lourenço Martins, Rui Sousa Mendes.
Tipo de material: TextoSeries SpringerBriefs in Applied Sciences and TechnologyEditor: Cham : Springer International Publishing : Imprint: Springer, 2016Edición: 1st ed. 2016Descripción: XII, 93 p. 10 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783319258553Tema(s): Engineering | Sports sciences | Graph theory | Statistics | Applied mathematics | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Graph Theory | Sport Science | Statistics and Computing/Statistics ProgramsFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 519 Clasificación LoC:TA329-348TA640-643Recursos en línea: Libro electrónicoTipo de ítem | Biblioteca actual | Colección | Signatura | Copia número | Estado | Fecha de vencimiento | Código de barras |
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Libro Electrónico | Biblioteca Electrónica | Colección de Libros Electrónicos | 1 | No para préstamo |
Introduction -- Social Network Analysis: Concepts and definitions -- Observational tools to collect data in team sports -- Micro Levels of analysis: Player´s centralities in the team -- Meso Level of analysis: Subgroups in Teams -- Macro Levels of analysis: Network of the team -- Argentina’s Network Analysis in FIFA World Cup 2014: A Case Study
Explaining how graph theory and social network analysis can be applied to team sports analysis, This book presents useful approaches, models and methods that can be used to characterise the overall properties of team networks and identify the prominence of each team player. Exploring the different possible network metrics that can be utilised in sports analysis, their possible applications and variances from situation to situation, the respective chapters present an array of illustrative case studies. Identifying the general concepts of social network analysis and network centrality metrics, readers are shown how to generate a methodological protocol for data collection. As such, the book provides a valuable resource for students of the sport sciences, sports engineering, applied computation and the social sciences.